How we decide, build, and measure.
Our method is not proprietary and we see no reason to pretend otherwise. What is rare is applying it with discipline. This page describes exactly what an engagement with us looks like, so you can hold us to it.
Intelligence work and judgement work.
Most enterprise work divides into two kinds. Intelligence work follows rules: processing, triaging, reconciling, drafting, checking. The rules can be intricate, but they are rules, and today's models handle this work reliably when the system around them is built well. Judgement work is different. It rests on experience: knowing which exception matters, when to escalate, which trade-off to accept, when the data is lying to you.
Every decision in our method comes back to drawing this line correctly for a specific workflow in a specific organization. Draw it too conservatively and you automate nothing meaningful. Draw it too aggressively and you discover the error in front of a customer or a regulator. Drawing it well is the actual skill, and it cannot be done from a slide. It requires sitting with the work.
The wedge, chosen deliberately.
The first AI project determines the fate of the program, because it either produces a number the CFO believes or it does not. So we choose it against three criteria, and we hold the line on them.
Well-defined
Clear inputs, explicit rules, output that can be verified without a committee.
High-volume
Enough repetition for the economics to be visible within a quarter.
Already externalized or backlogged
An outsourcing line that can be substituted cleanly, or work everyone agrees is not getting done. Either way, the baseline is real.
Ambitious, judgement-heavy showcase projects fail quietly and take the program's credibility with them. The modest workflow that produces a clean before-and-after funds everything that follows. This is the least glamorous advice we give, and the most valuable.
Map. Build. Run. Improve.
Map, weeks 1 to 3
Workflow study with the people who do the work. Cost baseline, feasibility, integration constraints, and the judgement line drawn explicitly. Output: a business case stated plainly enough for a CFO to challenge.
Build, typically weeks 4 to 10
One senior team, building on the Sprouto Agent Platform. Guardrails, escalation, and evaluation are part of the build, not the punch list. Working software in front of your team early, because feedback on real behavior beats feedback on static prototypes.
Run, from first go-live
Parallel running against the current process until the numbers justify the switch. Then production, monitored continuously, with a live view of the metrics we committed to. Humans stay in the loop where we agreed they would, and those checkpoints get reviewed, not forgotten.
Improve, every cycle
Evaluation suites rerun on every model upgrade. Scope expands when performance earns it. A system built this way gets better each quarter without a new project, which is the property that makes the economics compound.
Priced against the work, not the hours.
We scope engagements against outcomes with the success criteria agreed in writing before build begins: cost per transaction, cycle time, throughput, backlog cleared. Unit economics are reported against your measured baseline. Where a client wants to internalize the capability, we build their team up and hand over cleanly; where they want us to keep running the system, we do. We have no licensing agenda pushing either answer.
Built for the review, before the review.
ISO 27001 certified
Audited information security management across delivery and operations.
Human checkpoints, documented
Escalation paths documented before go-live, with kill-switch authority defined.
Full auditability
Every AI action logged, traceable, and reviewable. If your auditors ask what the system did on a Tuesday in March, there is an answer.
Explicit data boundaries
Contractual and technical. Least-privilege access as the default posture.